1. Field of the Invention
The invention relates to handwriting recognition. In particular, the invention relates to on-line handwriting recognition in a novel and improved way.
2. Description of the Related Art
The term “handwriting recognition” refers to a feature of a computer device or corresponding to receive intelligible written input. Handwriting recognition is often classified in two categories: off-line handwriting recognition and on-line handwriting recognition.
In off-line handwriting recognition, an image of written text is sensed e.g. from a piece of paper typically by means of optical scanning. Characters included in the written text are then recognized from the scanned image typically by means of suitable software.
In on-line handwriting, recognition text is written on e.g. a touch sensitive screen surface with e.g. a pen or a stylus, and the movements of the pen or stylus are sensed on-line. Characters drawn with the pen or stylus are interpreted or recognized by a software application. The touch sensitive screen may e.g. be integrated with an output display, or it may e.g. be adjacent to the output display. On-line handwriting recognition has proven particularly popular in various handheld devices, such as personal digital assistants (PDA), tablet personal computers (tablet PC), and lately also mobile telephones. The term “tablet PC” refers to a type of notebook computer that is equipped with a digitizer tablet and a stylus, and allows a user to handwrite text with the stylus.
Prior art on-line handwriting recognition techniques can be broadly categorized into three groups. The first group consists of techniques in which a user writes text more or less as usual, and a software application tries to learn the writing patterns of the user. An example of this technique is the handwriting recognition used by a personal digital assistant known as Apple Newton™.
The second group consists of techniques in which a set of pen strokes is predefined for each character. To draw a character, the user does not write as usual. Rather, the user must draw the predefined pen strokes. Examples of this technique include a recognition system known as Graffiti® and used earlier in personal digital assistants by Palm, and a recognition system known as JOT® by Communication Intelligence Corporation which is also used in various personal digital assistants including these days those by Palm. This second group of on-line handwriting recognition techniques is sometimes called character based handwriting recognition.
The third group consists of techniques in which a recognition system maintains a database of possible, typically thousands, shapes for each character. The system does not attempt to learn the writing patterns of the user, nor is the user required to draw predefined pen strokes. Rather, the user draws a character as he normally would, and the system searches the database for the closest match. An example of this technique is the handwriting recognition used in Microsoft Windows XP® operating system for tablet PCs.
However, all these prior art techniques have their problems. The first group of techniques requires the system to learn the writing patterns of the user. In practice this has proven extremely difficult and the existing applications tend to be unreliable. The second group of techniques requires the user to draw predefined patterns. Therefore the user is required to memorize these predefined patterns in order to be able write. The third group of techniques requires the system to maintain an extensive database, which is particularly problematic for compact handheld devices, which simply may not have enough resources for database maintenance and searches. Furthermore, the prior art techniques typically require the user to draw blindly. That is, the user cannot see the character as it is being drawn, even though some applications may provide a baseline or underline upon which to draw the actual character. Furthermore, the prior art techniques are particularly disadvantageous in situations where the user is being shaken or is otherwise moving. Such situations include for example a user riding a bus and trying to write on his personal digital assistant. Trying to draw predefined patterns blindly in such a situation is extremely difficult.
Therefore, the object of the present invention is to alleviate the problems described above and to introduce a solution that allows handwriting recognition that is both more reliable and easier to use than before.